微特电机 ›› 2026, Vol. 54 ›› Issue (9): 34-41.

• 驱动控制 • 上一篇    下一篇

基于平滑超螺旋滑模与RBF神经网络的PMSM位置伺服复合控制

刘  浩,金学伟,张  晨   

  1. 辽宁科技大学  机械工程与自动化学院,鞍山 114051
  • 出版日期:2026-09-28 发布日期:2026-09-28
  • 作者简介:刘浩(1999—),男,硕士研究生,研究方向为电机及其控制。 金学伟(1968—),男,博士,讲师,硕士生导师,主要研究方向为机电检测与控制。

Composite Position Servo Control of PMSM Based on Smooth Super-Twisting Sliding Mode Control and RBF Neural Network

LIU Hao,JIN Xuewei,ZHANG Chen   

  1. School of Mechanical Engineering and Automation,Liaoning University of Science and Technology,Anshan 114051,China
  • Online:2026-09-28 Published:2026-09-28

摘要:

针对永磁同步电机( permanent magnet synchronous motor,PMSM) 位置伺服系统在快速定位、目标附近平稳收敛及受载恢复过程中的动态性能要求, 构建一种由基于误差调度平滑超螺旋滑模控制( smooth super-twisting sliding mode control, SSTSMC) 的位置环和径向基函数 (radial basis function, RBF) 神 经 网络自适应比例积分(proportional-integral,PI) 控制速度环组成的复合控制策略。位置环以位置误差构造滑模变量,通过误差调度增益、连续饱和函数和局部积分补偿生成参考转速,在提高位置响应速度的同时抑制目标附近超调和反复修正。速度环采用基于RBF神经网络的自适应 PI 控制结构。基于MATLAB/Simulink 进行位置阶跃、变速跟踪和负载扰动仿真。结果表明,误差调度平滑超螺旋滑模控制与RBF自适应PI复合控制策略可减小位置阶跃末端超调和稳态误差,降低稳态速度波动及负载扰动引起的转速跌落,改善位置伺服系统的快速性、末端平稳性和扰动恢复性能。

关键词: 永磁同步电机, 三闭环伺服, 平滑超螺旋滑模控制, 径向基函数神经网络, 自适应比例积分, 负载扰动

Abstract:

To meet the dynamic performance requirements of permanent magnet synchronous motor ( PMSM) position servo systems in rapid positioning,smooth convergence near the target position,and recovery under load,a composite control strategy consisting of a position loop based on error-scheduled smooth super-twisting sliding mode control ( SSTSMC) and a radial basis function ( RBF) neural-network-based adaptive proportional-integral ( PI ) speed loop is constructed. In the position loop,a sliding-mode variable is constructed from the position error,and the reference speed is generated through error-scheduled gains, a continuous saturation function, and local integral compensation, thereby improving the position response speed while suppressing overshoot and repeated correction near the target position. The speed loop adopts an adaptive PI control structure based on the RBF neural network. Position-step,variable-speed tracking,and load-disturbance simulations are conducted in MATLAB / Simulink. The results show that the composite control strategy combining errorscheduled SSTSMC with RBF adaptive PI control can reduce the terminal overshoot and steady-state error of the positionstep response,suppress steady-state speed fluctuations and the speed drop caused by load disturbances, and improve the rapidity,terminal smoothness,and disturbance-recovery performance of the position servo system.

Key words: permanent magnet synchronous motor, three-loop servo, smooth super-twisting sliding mode control, radial basis function neural network, adaptive proportional-integral, load disturbance

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